Enterprises kick-start automation initiatives with small projects that are simple and don’t require many resources. These projects are highly successful and give organizations the confidence to automate at scale, with an expectation of 100% automation. However, most business processes involve a combination of rule-based and experience-based tasks making automation solutions complex. It is no surprise that 64% of the automation projects fail to deliver the expectations. Complex projects require a higher degree of automation, making time, resources, and cost savings elusive.
But does that mean enterprises should not opt for automation? Absolutely not. There is a large market potential for automation. According to Gartner, spending on RPA technology will reach $2.4 billion by 2022. And there are success stories across the globe, across industries that point to the massive benefits of automation. Virgin Trains deployed RPA to automatically refund customers for trains that were running late. It improved customer experience and reduced processing time and manual labor by 85%. Large banks have leveraged automation to uncover revenue leakage, increase the number of tasks that are done ‘first-time-right,’ etc., resulting in significant cost benefits.
Why is achieving 100% automation a challenge?
Processes have evolved with new rules and validations creeping in every quarter. Although an ideal path for a process is largely rule-based, large business processes include a multitude of variances and exceptions, however infrequently they may occur. While process owners, buoyed by the successes of pilots, expect 100% automation, the Automation CoE’s stare at the uphill task of having to account for the variances. The sheer effort needed in terms of design, development, and testing for the variances that could account for just 20% of the volumes might need 80% of the automation investment. This could make automation an impractical choice.
So, what can enterprises do to make automation a practical and effective solution?
Building a failproof solution path
Having delivered impactful automation for several hundreds of processes over the last decade, across automation platforms for large organizations in Banking, Financial Services, Insurance, Manufacturing, and Supply Chain, we have learned a key lesson. It is important for organizations to reiterate the question of “Why automation?” till they arrive at the root of their automation objectives. Akin to the techniques of Lean Six Sigma, it takes about five iterations to arrive at the key objectives that drive clarity into the solution and the approach, making it compelling to implement.
The key objectives for automation typically are to reduce costs, improve quality, improve the speed of processing, increase the scale of processing, improve operational resilience, and reduce risk. Businesses should be able to shortlist 2-3 core objectives that will help them sharpen the solution and approach. Is it high drivers of the cost that demands automation, or is the main objective to build resilience?
The next step is to identify core elements, platforms, and tools that will impact the automation strategy and implementation
- Refining the process and eliminating redundancies: It is essential to understand the WHAT and WHY of any process before planning to automate it. Most processes evolved over time and have become complex or, at the least, not efficient. They need to be refined and standardized to avoid the inheritance of complexity into automation.
- Choosing your horses for the courses:
- Standard RPA – If organizations have rule-based and repetitive processes, RPA works very well. Unattended automation is the most common type of RPA that is triggered on a system action or schedule, and it executes the steps independently thereon. The typical unattended process includes data entry, data validation, monthly reporting, scheduling, and queue management. Attended and hybrid automation are used when there is a combination of rule-based and experience-based tasks in which automation can act as virtual assistants by automating the rule-based tasks and relying on humans for decision making. All leading RPA platforms, be it UiPath, Blue Prism, Automation Anywhere, etc. provide this capability
- Intelligent RPA (RPA + OCR / ICR) – If the process consists of extracting scanned/ handwritten documents, then OCR/ ICR comes into picture, helping extract the required data fields for processing. Abby, HyperScience, Google Tesseract, etc., are platforms that can be integrated with RPA platforms to provide the additional power for automation.
- Hyper Automation – Based on the process complexity and feasibility, multiple add-on technologies can be utilized to automate the process, including AI/ ML, Data visualization tools, BPM/Workflow solutions third-party solutions, enhancing existing applications to achieve the intended goal results. For instance, a process that involves classification/ extraction from unstructured documents can leverage AI/ ML solution for classification and extraction while using RPA for preliminary collection of documents or post-processing activities
- Automation Implementation Roadmap: Build your automation roadmap accounting for the process dynamics – volume spike or dips, upcoming amalgamations if any, talent planning, complexities, or nuances to automate, and so forth. Most times, it augurs well to carve out a Minimum Viable Product catering to your critical mass and then iteratively expand the automation footprint. This way, the automation teams can assimilate the process better, the operations managers can plan better for utilizing their teams at the right junctures and focus on exceptions that need the experience and skill. It is important to give a few weeks for the automated processing to settle in before making those personnel reassignments.
- Team: Critical to the success of any project, the team must have a uniform understanding of work delivery, timeframes, key objectives, targets, and goals of the project and collaborate between the functions for successful implementation. Equally important is building a skill set with the right talent to align with the project’s requirements, technology (Standard RPA, Intelligent RPA, Hyper Automation, etc.), and methodology.
The road ahead
Although state-of-the-art automation might seem like a daunting task, it is achievable. There are definitive cases to prove the worth and benefits of automation, yet many organizations are reluctant based on the challenges and a few wrong steps that led to little or no RoI. The fact, however, is every day of delaying automation is a day of efficiency and productivity loss. To do automation right, organizations can lean on partners that help realize the potential of automation. by creating a value-driven automation approach.
Authored by Yogendra K